Real-time analysis of bulk material activity

ABSTRACT

Disclosed herein are methods and system for redistributing bulk material across a geographical area. A method for providing bulk material for a wellbore operation, the method comprising: forming a logistical model database to determine bulk material required for an at least one wellsite located in a geographical area; acquiring bulk material from a distribution center; verifying the bulk material acquired; and transporting bulk material for the wellbore operation. A method for providing bulk material for a wellbore operation, the method comprising: determining demand for bulk material across a geographical area; collecting data throughout a life cycle of bulk material; transmitting collected data to an off-site network comprising an adaptive machine; analyzing collected data via the off-site network thereby producing an output; providing bulk material to a wellsite based on output. A system comprising: bulk material transport; off-site network comprising an adaptive machine; sensor coupled to the bulk material transport.

BACKGROUND

Significant volumes of sand (118 MM tones in 2018) is mined anddelivered to remote wellsite locations to support the US stimulationservices market. The industry supply-chains that are required to supportthis are typically manual, paper driven and have very little by way ofautomation. The present disclosure, may be designed to leverage therecent containerization of sand and new and unique micro-locationtechnologies along with machine learning algorithms, which may allow usfor the optimization of the supply chain. The present disclosure mayallow for the sand inventory to be located at any point during its lifecycle, distribution center to the wellsite.

Maintaining security of supply at the well site is critical to efficientoperations. The present disclosure may provide automated and real-timevisibility to the sand-vessel, by location, sand-type and quantity.Knowing where the inventory may be in real time may enable for thesystem to rapidly match supply to demand. The present disclosure mayalso help redistribute bulk material to well-sites across a definedgeographical area thereby reducing and/or preventing disruptions and/oroversupply at a well-site or a plurality of well-sites.

BRIEF DESCRIPTION OF THE DRAWINGS

These drawings illustrate certain aspects of some of the presentdisclosure, and should not be used to limit or define the disclosure.

FIG. 1 illustrates an embodiment of a life cycle of bulk material.

FIG. 2 illustrates an embodiment of a bulk material transport anddistribution center.

FIG. 3 illustrates an embodiment of a wellbore assembly.

FIG. 4 illustrates a flow diagram depicting an example method fordetermining an optimal route for redistributing bulk material across adefined geographical area.

FIG. 5 illustrates an embodiment of an off-site network.

DETAILED DESCRIPTION

In an embodiment, one or more Oil & Gas Well sites may be underconsideration for exploration and/or production operations. A wellsiteadministrator may be evaluating the desirability of the well orpreparing a logistical plan for well operations.

Next, the administrator may use a logistical model database to determineinventory needs for the wellsite under consideration. In certainembodiments, the logistical model may contain historical inventory dataindexed by basin or area so that the engineer can look up nearbywell-sites and review inventory data, such as what inventory was needed,how much was needed, and when it was needed. Additionally oralternatively, the logistical model may be indexed by wellsiteproperties (e.g., lithology, depth) so that the engineer may use knownproperties of the planned wellsite to review historical information fromsimilar well-sites that may have comparable properties. In this way, theengineer may identify not only which inventory was used but may alsoanticipate which inventory items may be particularly well-suited to theanticipated wellsite environment.

The administrator may then estimate which bulk materials the wellsitewill need and when they will be needed. The administrator may thendevelop a logistical plan for which inventory items should be orderedand when to schedule their delivery to the wellsite. This informationmay be programmed locally at a wellsite or in central planning andscheduling tool. This information may also be transmitted to an off-sitenetwork 106 where the data may be stored and processed. This selectionmay be made for each wellsite in a given geographical area. Once alogistical plan is in place, well-site operations may begin. Thelogistical plan developed may be presented and revised throughout theprocess operation. In an embodiment, changes made to the well-siteoperations may lead to disruptions or oversupply events at a givenwell-site, or multiple well-sites located in a defined geographicalarea. As used herein, “disruptions” refer to an event when well-siteoperations may be shut down due to an insufficient amount of bulkmaterial required to perform said operation. As used herein,“oversupply” may refer to an event when bulk material may not beutilized at a well-site due to the surplus of said bulk material. Themethods and systems disclosed herein may help mitigate disruptions andoversupply to a well-site. Additionally, the methods and systemsdisclosed herein may help redistribute bulk material to well-sitesacross a defined geographical area thereby reducing and/or preventingdisruptions and/or oversupply at a well-site or a plurality ofwell-sites.

Bulk material may be used during wellsite operations. As used herein,“bulk material” may include liquids, solids, and/or gas, and is notlimited to those utilized during wellsite and/or other oilfieldoperations. One or more aspects of the present disclosure may relate toimplementations in which the bulk material may comprise sand, proppant,guar, water, combustion engine fuel, and/or other materials consumed inappreciable quantities at a wellsite, another oilfield location, andeven other locations not associated with oil and gas operations. In anembodiment, bulk material may be transported from a distribution centerand to a wellsite in any suitable manner. In an embodiment, bulkmaterial may be transported by way of a bulk material transport 200.

FIG. 1 illustrates an embodiment of the life cycle of bulk material 100.First, a bulk material transport may be routed to a distribution center.Once the bulk material transport arrives at the distribution center, avessel disposed on the bulk material transport may be loaded with thedesired type and quantity of bulk material for a given wellsiteoperation. Once the bulk material has been loaded into the vessel, abill of lading may then be generated. In an embodiment, a bill of ladingmay include data pertaining to the bulk material including type, size,amount, the like, and/or any combination thereof. In an embodiment, thebill of lading may be verified utilizing the sensor system and machinelearning algorithm at the off-site network. This may be advantageous, ascurrent methods and systems may not be capable of accurately andefficiently validating the bill of lading. Current methods and systemsmay comprise several disadvantages for verifying a bill of ladingincluding, but not limited to, requiring a substantial amount of time tomanually verify, personnel may not be properly trained to verify a billof lading thereby providing inaccurate verification, the wronginformation may be recorded, personnel may be incorrectly trained toverify a bill of lading thereby providing inaccurate verification, thewrong information may be recorded, information may be omitted, the like,and/or any combinations thereof.

Once the bill of lading has been verified, the bulk material transportmay then leave the distribution center. The bulk material transport maythen proceed to a wellsite. In an embodiment, the bulk materialtransport may be rerouted to a different wellsite based on theinformation collected and processed at an off-site network. This processof rerouting a bulk material transport may be discussed in greaterdetail below. Once the bulk material transport arrives at the determinedwellsite, heavy machinery may be used to remove the loaded vessel fromthe motor vehicle. In an embodiment, the loaded vessel may then beplaced at a location on the wellsite for use. Any suitable heavymachinery may be used. In an embodiment, heavy machinery may includefork lifts, cranes, tractors, loaders, the like, and/or any combinationsthereof.

Next, the heavy machinery may load an empty vessel onto the bulkmaterial transport. The bulk material transport may then depart from thewellsite and may be routed to a distribution center. Once the bulkmaterial transport arrives at a distribution center, the cycle may startover.

In an embodiment, once the bulk material transport arrives at awellsite, a time stamp may be recorded by a sensor. This time stamp maybe transmitted to an off-site network that may then start a detentionclock. As used herein, detention time may refer to the amount of timelapsed between when bulk material has arrived at a wellsite and when thebulk material has been off-loaded from the bulk material transport. Oncethe bulk material has been off-loaded, a monetary transaction betweenthe consumer and the provider may be executed at the instruction of anadaptive machine located at the off-site network. In an embodiment,inventory reconciliation may be instructed by the adaptive machine oncethe bulk material may be off-loaded from the bulk material transport.This may reduce the number of unbilled days. The present disclosure maybe advantageous as it may immediately record time stamps which in turnmay decrease the amount of time it may take to report the informationand provide an invoice to the consumer.

FIG. 2 illustrates an embodiment of a bulk material transport 200 andbulk material distribution center 210. In an embodiment, a bulk materialtransport 200 may include, but is not limited to, a motor vehicle 202, avessel 204, and a sensor 206. Any motor vehicle 202 capable oftransporting quantities of bulk material from a distribution center 210to a wellsite 300 may be used. Suitable motor vehicles 202 may include,but is not limited to, trucks, semi-trucks, rail cars, shippingcontainers, the like, and/or any combination thereof. In an embodiment,the motor vehicle 202 may be operated by a person 208 also referred toherein as “a driver”. In an embodiment, the bulk material transport 200may comprise a vessel 204. Any suitable vessel 204 capable of receiving,storing, and dispensing bulk material may be used. The vessel 204 may beof any suitable size, shape, thickness, and material and should not belimited herein. In an embodiment, the bulk material transport 200 maycomprise a sensor 206. Each sensor 206 may comprise at least onetransmitter and one receiver (not shown). In an embodiment, the bulkmaterial transport 200 may comprise a plurality of sensors 206. Sensors206 may be disposed on any suitable location within the bulk materialtransport 200. Suitable sensor 206 locations may include, but are notlimited to, on the vessel 204, in the motor vehicle 202, outside of themotor vehicle 202, on the chassis of motor vehicle 202, the like, and/orany combination thereof. Any suitable sensor 206 capable of measuring adesired parameter, transmitting the measured parameter to an off-sitenetwork 308 where the data may be further analyzed, may be used. In anembodiment, the sensor 206 may be any transmitter/receiver systemcapable of wirelessly transmitting data from the bulk material transport200 to an off-site network 222. Suitable sensors 206 may include, butare not limited to, GPS sensor, Bluetooth Low Energy (BLE), NetworkGateways, Anchor Points, Access Points, Radio-Frequency Identification(Active and/or Passive), Image Sensor, Load Cells, the like, and/or anycombinations thereof. Sensor 206 may be used to measure data at awellsite and/or at any point during the life cycle of a bulk material.

The data and information stored, collected, and processed at off-sitenetwork 222 may be used to route bulk material transport 200 to adistribution center 210. As used herein, a distribution center 210 mayrefer to any location in which a bulk material may be provided fordistribution/redistribution and use to consumers. In an embodiment,distribution center 210 may be located at a mine site where the bulkmaterial may be produced. Upon arrival at the distribution center 210,bulk material transport 200 may pass through an entry point 212. In anembodiment, distribution center 210 may comprise a plurality of entrypoints 212 and should not be limited herein. Entry point 212 as usedherein may also be referred to as a gate, a lane, and/or the like. Asensor 206 may time stamp said arrival and transmit the data to anoff-site network 222. This step may also include utilization of locationdata and image data to validate information collected by sensor.

The bulk material transport 200 may then be directed to a unit 216. Inan embodiment, unit 216 may be capable of storing and dispensing bulkmaterial. The bulk material transport 200 may then be positioned suchthat vessel 204 may be capable of receiving bulk material from unit 216.The bulk material may then be loaded into the vessel 204. In anembodiment, the bulk material may be loaded into vessel 204 by anysuitable means. Once loaded, a bill of lading may be produced and givento a driver of the motor vehicle 202. In an embodiment, a bill of ladingmay include data pertaining to the bulk material including composition,size, amount, the like, and/or any combination thereof. In anembodiment, the bill of lading may be verified utilizing the sensor 206system and machine learning algorithm at the off-site network. Propervalidation may be advantageous as it may ensure that the correctmaterial may be delivered and used to a given wellsite, delivery and useof an incorrect material may result in failure of an operation which maycause a large time delays and/or may damage the wellbore. In anembodiment, the motor vehicle 202 and/or the vessel 204 may comprise asensor 206 system that may produce an image or a sequence of images andtransmit said produced image or sequence of images to an off-sitenetwork 108. The off-site network 108 may comprise an machine learningalgorithm system that may be trained to determine the type of bulkmaterial loaded into the vessel 204 and/or the amount of bulk materialloaded into the vessel 204. In an embodiment, once the vessel 204 hasbeen filled with the desired quantity of bulk material, the driver 208then departs from the distribution center. The motor vehicle may thenpass through a gate as the vehicle leaves the distribution center 210.

Next, bulk material transport 200 may then proceed through an exit point218 thereby leaving distribution center 210. In an embodiment,distribution center 210 may comprise a plurality of exit points 218 andshould not be limited herein. Exit point 218 as used herein may also bereferred to as a gate, a lane, and/or the like. A sensor 206 may timestamp said departure and transmit the data to an off-site network 108for storage and processing. In an embodiment, the measured time stampsmay allow for the tracking of delays located at each filling station.

The bulk material transport may then proceed to a wellsite 306(referring to FIG. 3 ). In an embodiment, measurements and data may becollected throughout the bulk material life cycle 100. In an embodiment,the measurements and data may be collected, measured and recorded inreal-time. These measurements and data may be combined with othermeasurements and data collected and recorded at other sources. Sourcesfor additional measurements and data may include, but are not limitedto, wellsites, traffic data, weather, motor vehicle information, thelike, and/or any combination thereof. The data and measurements may beprocessed and an optimal destination and route may be determined. Thebulk material transport 200 may be rerouted to a different wellsitebased on the determined output. In an embodiment, optimizing bulkmaterial on each wellsite across multiple wellsites within a givengeographical area. In an embodiment, optimization of bulk material ateach wellsite may include, minimizing the travel time of a bulk materialfrom a distribution center to a wellsite. In an embodiment, optimizationof bulk material at each wellsite may include, minimizing the amount oftime a wellsite may be down due to an insufficient amount of bulkmaterial to perform an operation. In an embodiment, the bulk materialtransport 200 may be rerouted to a different wellsite. The driver 208may be notified of the route change in any suitable manner, includingbut not limited to, computers, desktops, laptops, tablets, hand heldelectronic devices, a navigation system, the like, and/or anycombinations thereof.

As noted above, additional data and/or measurements from a wellsite 300or a plurality of wellsites 300 may be transmitted, stored, andprocessed by off-site network 222. The additional data and/ormeasurements may be used to aid in determining the optimal route for abulk material transport 200. FIG. 3 illustrates an example wellsite 300that may be used for preparation and delivery of a treatment fluiddownhole. It should be noted that while FIG. 3 generally depicts aland-based operation, those skilled in the art will readily recognizethat the principles described herein are equally applicable to subseaoperations that employ floating or sea-based platforms and rigs, withoutdeparting from the scope of the disclosure.

Referring now to FIG. 3 , a fluid handling system 302 is illustrated.The fluid handling system 302 may be used for preparation of a treatmentfluid including the multi-functional diverter particulate and forintroduction of the treatment fluid into a wellbore 304. The fluidhandling system 302 may include mobile vehicles, immobile installations,skids, hoses, tubes, fluid tanks or reservoirs, pumps, valves, and/orother suitable structures and equipment. As illustrated, the fluidhandling system 302 may include a fluid supply vessel 306, pumpingequipment 308, and wellbore supply conduit 310. While not illustrated,the fluid supply vessel 306 may contain one or more components of thetreatment fluid (bulk material, the like, and/or any combinationsthereof) in separate tanks or other containers that may be mixed at anydesired time. Sensor may be located on tanks or other containers and maycontrol the amount of bulk material mixed, the rate at which it may bemixed, the like, and/or any combination thereof. Pumping equipment 308may be fluidically coupled with the fluid supply vessel 306 and wellboresupply conduit 310 to communicate the treatment fluid into wellbore 304.Fluid handling system 302 may also include surface and downhole sensors(not shown) to measure pressure, rate, temperature and/or otherparameters of treatment. Fluid handling system 302 may also include pumpcontrols and/or other types of controls for starting, stopping, and/orotherwise controlling pumping as well as controls for selecting and/orotherwise controlling fluids pumped during the injection treatment. Aninjection control system may communicate with such equipment to monitorand control the injection of the treatment fluid. As depicted in FIG. 3, the fluid supply vessel 306 and pumping equipment 308 may be above thesurface 312 while the wellbore 304 is below the surface 312. As will beappreciated by those of ordinary skill in the art, wellsite 300 may beconfigured as shown in FIG. 3 or in a different manner, and may includeadditional or different features as appropriate. By way of example,fluid handling system 302 may be deployed via skid equipment, marinevessel, or may be included of sub-sea deployed equipment.

Wellsite 300 may be used for introduction of any suitable treatmentfluid into wellbore 304 and should not be limited herein. Generally,wellbore 304 may include horizontal, vertical, slanted, curved, andother types of wellbore geometries and orientations. Without limitation,the treatment fluid may be applied through the wellbore 304 tosubterranean formation 314 surrounding any portion of wellbore 304. Asillustrated, the wellbore 304 may include a casing 316 that may becemented (or otherwise secured) to wellbore wall by cement sheath 318.Perforations 320 allow the treatment fluid and/or other materials toflow into and out of the subterranean formation 314. A plug 322, whichmay be any type of plug (e.g., bridge plug, etc.) may be disposed inwellbore 304 below the perforations 320 if desired. While FIG. 3illustrates use of treatment fluid in a cased section of wellbore 304,it should be understood that treatment fluid may also be used inportions of wellbore 304 that are not cased.

The treatment fluid including bulk material may be pumped from fluidhandling system 302 down the interior of casing 316 in wellbore 304. Asillustrated, well conduit 324 (e.g., coiled tubing, drill pipe, etc.)may be disposed in casing 316 through which the treatment fluid may bepumped. The well conduit 324 may be the same or different than thewellbore supply conduit 310. For example, the well conduit 324 may be anextension of the wellbore supply conduit 310 into the wellbore 304 ormay be tubing or other conduit that is coupled to the wellbore supplyconduit 310. The treatment fluid may be allowed to flow down theinterior of well conduit 324, exit the well conduit 324, and finallyenter subterranean formation 314 surrounding wellbore 304 by way ofperforations 320 through the casing 316 (if the wellbore is cased as inFIG. 3 ) and cement sheath 318. Without limitation, the treatment fluidmay be introduced into subterranean formation 314 whereby one or morefractures 326 may be created or enhanced in subterranean formation 314.For example, the treatment fluid may be introduced into subterraneanformation 314 at or above a fracturing pressure. As previously,described, the treatment fluid including the bulk material may be placedinto the subterranean formation 314 after a previous treatment has beenperformed such that additional locations in the subterranean formation314 may be treated. Without limitation, at least a portion of the bulkmaterials may be deposited in the subterranean formation 314.

As previously described, a variety of treatments may be performed usingthe bulk material. Suitable subterranean treatments may include, but arenot limited to, drilling operations, production stimulation operations(e.g., fracturing, acidizing), and well completion operations (e.g.,gravel packing or cementing). These treatments may generally be appliedto the subterranean formation 314.

The well treatment may include a fracturing treatment in which one ormore fractures 326 may be created in subterranean formation 314.Fracture 326 is shown extending from wellbore 304. The fracturing of thesubterranean formation 314 may be accomplished using any suitabletechnique. By way of example, a fracturing treatment may includeintroducing a fracturing fluid into subterranean formation 314 at orabove a fracturing pressure. The fracturing fluid may be introduced bypumping the fracturing fluid through casing 316, perforations 320, andinto subterranean formation 314 surrounding wellbore 304. Alternatively,a jetting tool (not shown) may be used to initiate the fracture 326. Thefracturing fluid may include proppant particulates which may bedeposited on the fracture 326 to form a proppant pack 328. A sensors ora plurality of sensors (not shown) may be disposed throughout wellsite300. In an embodiment, sensors may be disposed on a blender, fluidhandling system, downhole, a wellhead, a flow line leading to the well,a flow line leading from the well, the like, and/or any combinationsthereof. Sensors may be disposed at any suitable location on wellsite300 and should not be limited herein. Any suitable sensor capable ofmeasuring a desired parameter, transmitting the measured parameter to anoff-site network 222 where the data may be further analyzed, may beused. In an embodiment, the sensor may be any transmitter/receiversystem capable of wirelessly transmitting data from wellsite 300 to anoff-site network 222. Suitable sensors may include, but are not limitedto, GPS sensor, Bluetooth Low Energy (BLE), Network Gateways, AnchorPoints, Access Points, Radio-Frequency Identification (Active and/orPassive), Image Sensor, Load Cells, the like, and/or any combinationsthereof.

FIG. 4 illustrates a flow diagram depicting an example method fordetermining an optimal route for redistributing bulk material across adefined geographical area 400. In an embodiment, data may be measuredand collected at a wellsite. Any suitable data may be measured andcollected, including but not limited to, bulk material consumption, typeof operation to be performed, type of bulk material required for desiredoperation, amount of bulk material required for desired operation, . . ., the like, and/or any combination thereof [any others?] Optionally,data may be measured and collected throughout the life cycle of a bulkmaterial 300 (referring to FIG. 3 ). Any suitable data may be measuredand collected, including but not limited to, time stamps upon arrivaland departure, type of bulk material being loaded, amount of bulkmaterial being loaded, well disruptions, well equipment failure, theminimum amount of material required for a given wellsite, the maximumamount of material required for a given wellsite, excess amount of bulkmaterial at a wellsite at a given time, the like, and/or any combinationthereof. Optionally, data may be measured and collected from additionalsources. Such data may include, but is not limited to, weather, trafficconditions, vehicle conditions, road conditions, wellsite conditions,wellbore conditions, the like, and/or any combination thereof. In anembodiment, data may be measured and collected at a wellsite, aplurality of wellsites, throughout the life cycle of bulk material, andfrom additional sources, and/or any combination thereof. The measureddata may then be transmitted to off-site network 108 for storage andprocessing. Based on the output of the processed data, an optimalwellsite location and route to said wellsite location may be determined.This information may then be transmitted to driver 208. Driver 208 maythen reroute bulk material transport to the newly identified wellsitelocation. In an embodiment, the determined information may betransmitted to any end user including, but not limited to, wellsiteplanners, load planners, drivers, the like, and/or any combinationsthereof.

Data and/or measurements may be collected at any point throughout thelife cycle of bulk material. The collected data and/or measurements maybe transmitted to off-site network 222 for further processing and/orstorage. off-site network 222 may process the collected data in anysuitable manner for determining the optimal location and route for agiven load of bulk material. In an embodiment, the processor maydetermine if the bulk material located at the wellsite is sufficient forcompleting the current stage. FIG. 5 illustrates an embodiment ofoff-site network 222. Off-site network 222 may comprise anyinstrumentality or aggregate of instrumentalities operable to compute,classify, process, transmit, receive, retrieve, originate, switch,store, display, manifest, detect, record, reproduce, handle, or utilizeany form of information, intelligence, or data for business, scientific,control, or other purposes. In certain embodiments, an off-site network222 may comprise hardware for executing instructions, such as thosemaking up a computer program. In certain embodiments, a off-site network222 may be coupled to a memory device 502 where data, software,programming, and/or executable instructions are stored. Such memorydevices may comprise a hard drive, random access memory (RAM), read-onlymemory (ROM), or other similar storage media known in the art, and maycomprise a set of instructions that when executed by the off-sitenetwork 222 may cause the off-site network 222 to perform one or more ofthe actions, calculations, or steps of the methods of the presentdisclosure described herein. In certain embodiments, a computerprocessor may comprise one or more arithmetic logic units (ALUs); be amulti-core processor; or comprise one or more processors.

In an embodiment, the off-site network 222 may execute instructions, forexample, to generate output data 504 based on data inputs 504. Forexample, the off-site network 222 may include a processor 508 that mayexecute or interpret software, scripts, programs, functions,executables, or other modules. In certain embodiments, input datareceived by the off-site network 222 may comprise data from one or moresensors sensing one or more signals from a detectable component of theMOF of the present disclosure. In certain embodiments, output datagenerated by the off-site network 222 may comprise imaging data and/orimages that may be processed by an optical computing device. Images maybe used as a “sensor” in this process. Image data may be utilized bydeep learning algorithm to provide precise results that may be difficultto achieve otherwise. In an embodiment, the adaptive machine may becapable: of validating a bill of lading as described above.

The off-site network 222 may communicate by any type of communicationchannel, connector, data communication network, or other link 506. Incertain embodiments, for example, the communication may comprise awireless or a wired network, a Local Area Network (LAN), a Wide AreaNetwork (WAN), a private network, a public network (such as theInternet), a WiFi network, a network that comprises a satellite link, aserial link, a wireless link (e.g., infrared, radio frequency, orothers), a parallel link, another type of data communication network, orany combination thereof.

In an embodiment, off-site network 222 may use a computer algorithm toestimate the redistribution of bulk material across a definedgeographical area. The defined geographical area may comprise at leastone wellsite. In an embodiment, the defined geographical area maycomprise a plurality of wellsites. The algorithm may be part of anadaptive machine configured to use the amount of bulk material requiredfor a process, the amount of bulk material located at a wellsite, theconsumption rate of bulk material at a wellsite, the time required todeliver bulk material to a wellsite, to estimate the redistribution ofbulk material across a defined geographical area. The adaptive machinemay comprise “artificial intelligence” that may utilize algorithms tolearn via inductive inference based on observing data that representsincomplete information about statistical phenomenon and generalize it torules and make predictions on missing attributes or future data.Further, the adaptive machine may perform pattern recognition, in whichthe adaptive machine may “learn” to automatically recognize complexpatterns, to distinguish between exemplars based on their differentpatterns, and to make intelligent predictions on their class. In anembodiment, the adaptive machine may utilize a machine learningalgorithm that may be trained using samples of predeterminedcharacteristics of interest, and thereby generating a virtual library.As the virtual library available to the machine learning algorithmbecomes larger, the machine learning algorithm may become more capableof accurately predicting the redistribution of bulk material.Furthermore, with sufficient training, the machine learning algorithmmay more accurately predict the optimal redistribution of bulk materialacross a defined geographical area, even in the presence of unknownanalytes.

In some embodiments, data and/or measurements collected using theoptical computing device may be archived along with data associated withoperational parameters being logged at a job site and within the lifecycle of bulk material. In addition, the data and information may becommunicated (wired or wirelessly) to a remote location by acommunication system (e.g., satellite communication or wide area networkcommunication) for further analysis. Automated control with a long-rangecommunication system may further facilitate the optimization ofdistributed bulk material across a defined geographical area.

In an embodiment, adaptive machine 510 may facilitate the rerouting ofbulk material transport. Adaptive machine 510 may process a wide varietyof variables and possible outcomes so that an optimal route for bulkmaterial transport may be produced. In an embodiment, adaptive machine510 may collect the demand of bulk material required for a wellsite or aplurality of wellsites. Adaptive machine 510 may then rank the demand ofbulk material. The demand of bulk material may be ranked based on thetotal cost of ownership and the time it may take to deliver the bulkmaterial. Once the demand has been ranked, the adaptive machine 510 maythen allocate the demand of bulk material utilizing a transportationmanagement system based on the determined rank. The transportationmanagement system may also be analyzed by the adaptive machine 510. Inan embodiment, the transportation management system may comprise aplurality of bulk material transports. The analysis may comprisedetermining which bulk material transports have already been assignedloads, how long the bulk material transports may have been at thedistribution center, how long it may take the bulk material transportsto deliver the bulk material to a wellsite. The adaptive machine 510 mayalso provide a visual map of each load of bulk material and its currentlocation. Optionally, adaptive machine 510 may determine the minimum andmaximum bulk material requirement for a wellsite based on a number offactors. Factors may include, but are not limited to, location of thedistribution center, location of the wellsite, routes from thedistribution center to the wellsite, traffic, weather, plannedconsumption rate of bulk material at the well site, amount of bulkmaterial currently at the wellsite, the like, and/or any combinationsthereof. Processing collected data using the adaptive machine 510 asnoted above may be advantageous as it may accurately predict which bulkmaterial transports may service a wellsite in real-time. This is merelyan example of the processing an adaptive machine 510 may use to optimizethe redistribution of bulk material across a defined geographical areaand should not limited the present disclosure herein.

Adaptive machine 510 may then output the determined optimal route to adisplay device. Any suitable display device may be used and should notbe limited herein. Suitable display devices may include, computers,desktops, laptops, tablets, hand held electronic devices, a navigationsystem, the like, and/or any combinations thereof.

Accordingly, this disclosure describes methods, systems, and apparatusesthat may use the disclosed screws. The methods, systems, and apparatusesmay include any of the following statements:

Statement 1. A method for providing bulk material for a wellboreoperation, the method comprising: forming a logistical model database todetermine the bulk material required for an at least one wellsitelocated in a geographical area; acquiring the bulk material from adistribution center; verifying the bulk material acquired; andtransporting the bulk material for the wellbore operation.

Statement 2. The method of statement 1, wherein transporting the bulkmaterial further comprises: selecting a first wellsite within thegeographical area; determining a first route to transport the bulkmaterial required to the first wellsite; analyzing the bulk materialrequired for a second wellsite within the geographical area, wherein thebulk material required for the first wellsite is the same as the bulkmaterial required for the second wellsite; determining a second route totransport the bulk material required to the second wellsite; comparingthe first route and the second route; determining an optimal route forthe bulk material required; and transporting the bulk material requiredto the first wellsite or the second wellsite via the optimal route.

Statement 3. The method of statement 1 or 2, wherein the first route,the second route, and the optimal route are determined using an off-sitenetwork comprising an adaptive machine.

Statement 4. The method of any of the preceding statements, wherein theoptimal route is transmitted from the off-site network to a displaydevice thereby notifying a bulk material transport operator.

Statement 5. The method of any of the preceding statements, whereincomparing the first route and the second route further comprisescomparing at least one parameter selected from the group consisting oflocation of the distribution center, location of each wellsite, routesfrom the distribution center to each wellsite, traffic patterns,weather, planned consumption rate of the bulk material at each wellsite,amount of bulk material currently at each wellsite, a maximum amount ofbulk material required at each wellsite, minimum amount of bulk materialrequired at each wellsite, and any combinations thereof.

Statement 6. The method of any of the preceding statements, wherein theoptimal route minimizes the transportation time of the bulk materialfrom the distribution center to the first wellsite or from thedistribution center to the second wellsite.

Statement 7. The method of any of the preceding statements, whereinacquiring the bulk material further comprises: providing a bulk materialtransport comprising a vessel capable of holding the bulk material;operating the bulk material transport to enter a bulk materialdistribution center; and loading the bulk material into the vessel.

Statement 8. The method of any of the preceding statements, whereinverifying the bulk material further comprises: collecting data at thedistribution center via an at least one sensor located on a bulkmaterial transport; transmitting the collected data to an off-sitenetwork comprising an adaptive machine; analyzing the collected data todetermine the bulk material acquired; and comparing the acquired bulkmaterial with the required bulk material.

Statement 9. The method of any of the preceding statements, wherein theadaptive machine is capable of verifying that the acquired bulk materialis the required bulk material.

Statement 10. The method of any of the preceding statements, wherein thecollected data comprises at least one parameter selected from the groupconsisting of a type of bulk material, the bulk material size, an amountof the bulk material, and any combinations thereof.

Statement 11. A method for providing bulk material for a wellboreoperation, the method comprising: determining demand for the bulkmaterial across a geographical area; collecting data throughout a lifecycle of the bulk material; transmitting the collected data to anoff-site network comprising an adaptive machine; analyzing the collecteddata via the off-site network thereby producing an output; providing thebulk material to a wellsite based on the output.

Statement 12. The method of statement 11, wherein the life cycle of thebulk material comprises: routing a bulk material transport to adistribution center based on the determined demand; loading the bulkmaterial transport with the bulk material; verifying the bulk materialloaded into the bulk material transport; selecting a route from thedistribution center to a wellsite; transporting the bulk material to thewellsite; and unloading the bulk material at the wellsite.

Statement 13. The method of statement 11 or 12, wherein the routeselected minimizes the transportation time of the bulk material.

Statement 14. The method of any of statements 11 to 13, wherein the datacollected comprises at least one parameter selected from the groupconsisting of composition of the bulk material, size of the bulkmaterial, location of the distribution center, location of the wellsite,routes from the distribution center to the wellsite, traffic patterns,weather, planned consumption rate of the bulk material at the wellsite,amount of bulk material currently at the wellsite, and any combinationsthereof.

Statement 15. The method of any of statements 11 to 14, wherein theoutput comprises at least one determined parameter selected from thegroup consisting of a maximum amount of bulk material required at thewellsite, a minimum amount of bulk material required at the wellsite, acomposition of the bulk material, size of the bulk material, amount ofthe bulk material, and any combinations thereof.

Statement 16. A system, the system comprising: a bulk material transportcapable of moving bulk material from one location to another location;an off-site network comprising an adaptive machine; and a sensor coupledto the bulk material transport capable of collecting data andtransmitting data to the off-site network.

Statement 17. The system of statement 16, wherein the collected data iswirelessly transmitted from the sensor to the off-site network.

Statement 18. The system of statement 16 or 17, wherein the off-sitenetwork comprises an algorithm capable of determining the demand of abulk material across a geographical area.

Statement 19. The system of any of the preceding statements, wherein thealgorithm is a machine learning algorithm.

Statement 20. The system of any of the preceding statements, furthercomprising a plurality of sensors coupled to the bulk material transportcapable of collecting data measured at a wellsite, during a life cycleof a bulk material, from an additional source, wherein the additionalsource provides at least one data point selected from the groupconsisting of traffic data, weather data, motor vehicle data, roadconditions, and any combinations thereof.

It should be understood that the compositions and methods are describedin terms of “comprising,” “containing,” or “including” variouscomponents or steps, the compositions and methods can also “consistessentially of” or “consist of” the various components and steps.Moreover, the indefinite articles “a” or “an,” as used in the claims,are defined herein to mean one or more than one of the element that itintroduces.

For the sake of brevity, only certain ranges are explicitly disclosedherein. However, ranges from any lower limit may be combined with anyupper limit to recite a range not explicitly recited, as well as, rangesfrom any lower limit may be combined with any other lower limit torecite a range not explicitly recited, in the same way, ranges from anyupper limit may be combined with any other upper limit to recite a rangenot explicitly recited. Additionally, whenever a numerical range with alower limit and an upper limit is disclosed, any number and any includedrange falling within the range are specifically disclosed. Inparticular, every range of values (of the form, “from about a to aboutb,” or, equivalently, “from approximately a to b,” or, equivalently,“from approximately a-b”) disclosed herein is to be understood to setforth every number and range encompassed within the broader range ofvalues even if not explicitly recited. Thus, every point or individualvalue may serve as its own lower or upper limit combined with any otherpoint or individual value or any other lower or upper limit, to recite arange not explicitly recited.

Therefore, the present disclosure is well adapted to attain the ends andadvantages mentioned as well as those that are inherent therein. Theparticular examples disclosed above are illustrative only, as thepresent disclosure may be modified and practiced in different butequivalent manners apparent to those skilled in the art having thebenefit of the teachings herein. Although individual examples arediscussed, the disclosure covers all combinations of all those examples.Furthermore, no limitations are intended to the details of constructionor design herein shown, other than as described in the claims below.Also, the terms in the claims have their plain, ordinary meaning unlessotherwise explicitly and clearly defined by the patentee. It istherefore evident that the particular illustrative examples disclosedabove may be altered or modified and all such variations are consideredwithin the scope and spirit of the present disclosure. If there is anyconflict in the usages of a word or term in this specification and oneor more patent(s) or other documents that may be incorporated herein byreference, the definitions that are consistent with this specificationshould be adopted.

What is claimed is:
 1. A method for providing bulk material for awellbore operation, the method comprising: forming a logistical modeldatabase to determine the bulk material required for an at least onewellsite located in a geographical area; acquiring the bulk materialfrom a distribution center; capturing images of the bulk material withan image sensor to verify the bulk material acquired; transporting thebulk material for the wellbore operation by: selecting a first wellsitewithin the determined geographical area; determining a first route totransport the bulk material required to the first wellsite; analyzingthe bulk material required for a second wellsite within the geographicalarea, wherein the bulk material required for the first wellsite is thesame as the bulk material required for the second wellsite; determininga second route to transport the bulk material required to the secondwellsite; comparing the first route and the second route; determining anoptimal route for the bulk material required; and transporting the bulkmaterial required to the first wellsite or the second wellsite via theoptimal route; wherein the first route, the second route, and theoptimal route are determined using an off-site network comprising anadaptive machine; wherein the adaptive machine utilizes an algorithm tolearn via inductive inference and perform pattern recognition; whereinthe algorithm is configured to determine the amount of the bulk materialrequired for a process, the amount of the bulk material located at thefirst or second wellsite, the consumption rate of the bulk material atthe first or second wellsite, the time required to deliver bulk materialto the first or second wellsite, or to estimate the redistribution ofbulk material across the defined geographical area; tracking theposition of the bulk material with a GPS sensor as it is transported;and tracking the proximity of the bulk material to the first or secondwellsite with a Bluetooth low-energy sensor.
 2. The method of claim 1,wherein the optimal route is transmitted from the off-site network to adisplay device thereby notifying a bulk material transport operator. 3.The method of claim 1, wherein comparing the first route and the secondroute further comprises comparing at least one parameter selected fromthe group consisting of location of the distribution center, location ofeach wellsite, routes from the distribution center to each wellsite,traffic patterns, weather, planned consumption rate of the bulk materialat each wellsite, amount of bulk material currently at each wellsite, amaximum amount of bulk material required at each wellsite, minimumamount of bulk material required at each wellsite, and any combinationsthereof.
 4. The method of claim 1, wherein the optimal route minimizesthe transportation time of the bulk material from the distributioncenter to the first wellsite or from the distribution center to thesecond wellsite.
 5. The method of claim 1, wherein acquiring the bulkmaterial further comprises: providing a bulk material transportcomprising a vessel capable of holding the bulk material; operating thebulk material transport to enter a bulk material distribution center;and loading the bulk material into the vessel.
 6. The method of claim 1,wherein capturing images of the bulk material with an image sensor toverify the bulk material further comprises: collecting data at thedistribution center via the at least one image sensor located on a bulkmaterial transport; transmitting the collected data to an off-sitenetwork comprising the adaptive machine; analyzing the collected data todetermine the bulk material acquired; and comparing the acquired bulkmaterial with the required bulk material.
 7. The method of claim 6,wherein the adaptive machine is capable of verifying that the acquiredbulk material is the required bulk material.
 8. The method of claim 6,wherein the collected data comprises at least one parameter selectedfrom the group consisting of a type of bulk material, the bulk materialsize, an amount of the bulk material, and any combinations thereof. 9.The method of claim 1, wherein the adaptive machine additionally ranksthe demand of bulk material based on the total cost of ownership and thetime it may take to deliver the bulk material.
 10. The method of claim9, wherein the adaptive machine allocates the demand of bulk materialutilizing a transportation management system based on the determinedrank.
 11. The method of claim 1, wherein the adaptive machine provides avisual map of each load of bulk material and its current location.
 12. Amethod for providing bulk material for a wellbore operation, the methodcomprising: determining demand for the bulk material across ageographical area; collecting data throughout a life cycle of the bulkmaterial; transmitting the collected data to an off-site networkcomprising an adaptive machine; wherein the adaptive machine utilizes analgorithm to learn via inductive inference and perform patternrecognition; wherein the algorithm is configured to determine the amountof the bulk material required for a process, the amount of the bulkmaterial located at a wellsite, the consumption rate of the bulkmaterial at a wellsite, the time required to deliver the bulk materialto a wellsite, or to estimate the redistribution of the bulk materialacross the defined geographical area; analyzing the collected data viathe off-site network with the adaptive machine thereby producing anoutput; acquiring the bulk material from a distribution center;capturing images of the bulk material with an image sensor to verify thebulk material acquired; transporting the bulk material for the wellboreoperation by selecting a wellsite within the determined geographicalarea; determining an optimal route to transport the bulk materialrequired to the wellsite; tracking the position of the bulk materialwith a GPS sensor as it is transported; tracking the proximity of thebulk material to the wellsite with a Bluetooth low-energy sensor; andproviding the bulk material to the wellsite based on the output.
 13. Themethod of claim 12, wherein the life cycle of the bulk materialcomprises: routing a bulk material transport to a distribution centerbased on the determined demand; loading the bulk material transport withthe bulk material; verifying the bulk material loaded into the bulkmaterial transport with the image sensor; selecting a route from thedistribution center to the wellsite; and unloading the bulk material atthe wellsite.
 14. The method of claim 13, wherein the route selectedminimizes the transportation time of the bulk material.
 15. The methodof claim 12, wherein the data collected comprises at least one parameterselected from the group consisting of composition of the bulk material,size of the bulk material, location of the distribution center, locationof the wellsite, routes from the distribution center to the wellsite,traffic patterns, weather, planned consumption rate of the bulk materialat the wellsite, amount of bulk material currently at the wellsite, andany combinations thereof.
 16. The method of claim 12, wherein the outputcomprises at least one determined parameter selected from the groupconsisting of a maximum amount of bulk material required at thewellsite, a minimum amount of bulk material required at the wellsite, acomposition of the bulk material, size of the bulk material, amount ofthe bulk material , and any combinations thereof.
 17. A system, thesystem comprising: a bulk material transport capable of moving bulkmaterial from one location to another location; an off-site networkcomprising an adaptive machine; wherein the adaptive machine utilizes analgorithm to learn via inductive inference and perform patternrecognition; wherein the algorithm is configured to determine the amountof bulk material required for a process, the amount of bulk materiallocated at a wellsite, the consumption rate of bulk material at awellsite, the time required to deliver bulk material to a wellsite, orto estimate the redistribution of bulk material across a definedgeographical area; an image sensor coupled to the bulk materialtransport capable of collecting data and transmitting data to theoff-site network; a GPS sensor configured to track the bulk material asit is transported; a Bluetooth low-energy sensor to track the proximityof the bulk material to a target location.
 18. The system of claim 17,wherein the collected data is wirelessly transmitted from the sensor tothe off-site network.
 19. The system of claim 17, wherein the algorithmis additionally capable of determining the demand of a bulk materialacross a geographical area.
 20. The system of claim 17, furthercomprising a plurality of sensors coupled to the bulk material transportcapable of collecting data measured at a wellsite, during a life cycleof a bulk material, from an additional source, wherein the additionalsource provides at least one data point selected from the groupconsisting of traffic data, weather data, motor vehicle data, roadconditions, and any combinations thereof.